CN113221067A - Method and system for cross validation of weather data of occultation and microwave radiometer - Google Patents

Method and system for cross validation of weather data of occultation and microwave radiometer Download PDF

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CN113221067A
CN113221067A CN202110453718.6A CN202110453718A CN113221067A CN 113221067 A CN113221067 A CN 113221067A CN 202110453718 A CN202110453718 A CN 202110453718A CN 113221067 A CN113221067 A CN 113221067A
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高超
柳聪亮
刘黎军
王志强
韩佳
何杰颖
孙越强
杜起飞
白伟华
李伟
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National Space Science Center of CAS
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Abstract

The invention discloses a method and a system for cross validation of weather data of a occultation and microwave radiometer, wherein the method comprises the following steps: acquiring observation data of a microwave radiometer, occultation observation data and time-space data thereof and preprocessing; carrying out data matching on the preprocessed observation data based on the space-time data to obtain observation data matched with the microwave radiometer and the occultation space-time; calculating a curve angle profile by adopting an Abel integral forward modeling; carrying out comparison statistical analysis on the bending angle profile in the course of operation and the bending angle profile of occultation observation data; calculating the brightness temperature by forward modeling by adopting a radiation transmission model; comparing and analyzing the actual brightness temperature with the brightness temperature observed by the microwave radiometer; detecting whether the two kinds of observed data meet the accuracy consistency standard or not; judging whether the weather data set accords with the standard, and selecting the weather data set; otherwise, correcting; and generating a space-time continuous long-time sequence climate data set fused with the microwave radiometer and the occultation data based on the climate data set.

Description

Method and system for cross validation of weather data of occultation and microwave radiometer
Technical Field
The invention relates to the field of earth atmosphere detection technology and meteorological climate application thereof, in particular to a method and a system for cross validation of weather data of a occultation and microwave radiometer.
Background
Global climate change monitoring is a common scientific and technological problem in countries in the world, and the development of satellite climate science is promoted by the accumulation of meteorological satellite detection data. However, "drift" of atmospheric observations from different detectors of different satellites is one of the major challenges in satellite climate.
The satellite-borne microwave radiometer is a kind of under-satellite point scanning passive earth atmosphere remote sensing detecting instrument, it inverses the thermodynamic parameters of atmospheric temperature and humidity by observing the bright temperature information of atmosphere, and its detecting data has the advantages of high space-time resolution, global continuity coverage, etc. However, the difference of different loading performance and calibration methods of different satellites is a negative factor influencing the accuracy and long-term consistency of climate data of the microwave radiometer, and restricts the climate monitoring application of detection data of the microwave radiometer.
Researches show that the occultation detection technology has the advantages of high vertical resolution, self-calibration, long-term stability and the like, has the potential of providing a reference climate data set, and can be used as calibration reference data of passive microwave remote sensing data. Especially in the height range of 8-20km, the occultation detection data has high precision and good long-term consistency, and is applied to the analysis of the global temperature change trend in the height range. However, the horizontal resolution of the occultation detection data is low, the global continuous coverage satellite difference is low, and a hundred-star-level occultation constellation network is required to perform atmospheric detection to meet the meteorological application with high space-time resolution.
The satellite-borne microwave radiometer and the occultation climate data are fused and applied, and the global long-term climate monitoring with high space-time resolution and good data quality consistency can be realized. Cross validation of weather data quality of two detection technologies is one of the key problems of their fusion applications.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a method and a system for cross-verifying climate data of a occultation and microwave radiometer for establishing a high-space-time-resolution long-term consistent fusion climate data set by integrating the advantages of the occultation and the microwave radiometer climate data, and realizes cross-verification of the occultation and the microwave radiometer climate data and quality control of the occultation and the microwave radiometer climate data.
In order to achieve the purpose, the invention provides a method for cross-verifying climate data of a occultation and microwave radiometer, which comprises the following steps:
acquiring observation data of a microwave radiometer, occultation observation data and time-space data thereof; the observation data of the microwave radiometer comprise: bright temperature data, temperature profile, humidity profile and pressure profile; the occultation observation data includes: a curved angle profile, a temperature profile, a humidity profile, and a pressure profile;
preprocessing the observation data of the microwave radiometer and the occultation observation data, and rejecting abnormal observation data;
carrying out data matching on the preprocessed observation data based on the space-time data to obtain observation data matched with the microwave radiometer and the occultation space-time;
calculating a bending angle profile by adopting Abel integral forward modeling based on temperature, humidity and pressure profiles of the microwave radiometer matched with time and space;
comparing the calculated bending angle profile with the bending angle profile of the occultation observation data, and performing statistical analysis to obtain a bending angle relative deviation mean value and a bending angle relative deviation standard deviation;
based on the occultation temperature, humidity and pressure profiles of space-time matching, forward modeling is adopted to calculate the brightness temperature by adopting a radiation transmission model;
comparing and analyzing the actual bright temperature with the bright temperature observed by the microwave radiometer to obtain an absolute value of a bright temperature difference value;
detecting whether the two kinds of observation data meet the precision consistency standard or not based on the bending angle relative deviation mean value, the bending angle relative deviation standard deviation and the bright temperature difference value absolute value; judging coincidence, and selecting occultation observation data, microwave radiometer observation data matched with space and time and selecting the occultation observation data and the space and time data into a climate data set; otherwise, correcting the observation data of the microwave radiometer by combining the background atmosphere information and the occultation observation data, and selecting the occultation observation data, the corrected observation data of the microwave radiometer and the time-space data of the observation data into a climate data set;
and generating a space-time continuous long-time sequence climate data set fused with the microwave radiometer and the occultation data based on the climate data set.
As an improvement of the above method, the spatiotemporal data comprises: the microwave radiometer observes the world time of data, the corresponding longitude, latitude and barometric pressure three-dimensional grid point data and the potential height of an observation pixel point; the world time of the occultation event, the longitude and latitude of the occultation event location, the radius of curvature of the tangent point, the geodesic gap, the influencing parameters and their average altitude profile.
As an improvement of the method, the preprocessed observation data are subjected to data matching based on the space-time data to obtain observation data matched with a microwave radiometer and a occultation space-time; the method specifically comprises the following steps:
world time t based on occultation of occultation eventroAnd the universal time t of observation data of the microwave radiometermThe time difference Δ t is calculated as:
Δt＝|tm-tro|；
occultation event location longitude based
Figure BDA0003039728520000021
And latitude λroLongitude of observation data pixel of microwave radiometer
Figure BDA0003039728520000022
And latitude λmThe calculated distance difference Δ s is:
Figure BDA0003039728520000031
wherein R is the average earth radius;
and carrying out data matching on the preprocessed data according to a space-time matching standard that the time difference delta t is less than 90 minutes and the distance difference delta s is less than 100km, so as to obtain observation data matched with the microwave radiometer and the occultation space-time.
As an improvement of the method, the temperature, humidity and pressure profiles of the microwave radiometer based on the space-time matching are calculated by adopting an Abel integral forward algorithm; the method specifically comprises the following steps:
calculating a refractive index profile from the temperature, humidity and pressure profile data;
n＝1+N×10-6
wherein N is a refractive index, N is a refractive index, and N satisfies the following formula:
Figure BDA0003039728520000032
wherein T is temperature, PdAt atmospheric dry pressure, PwIs the water vapor pressure;
calculating the altitude H corresponding to the ith air pressure layer according to the following formulaiAnd further obtaining an average altitude profile:
Figure BDA0003039728520000033
wherein, the standard value g of the gravity acceleration0G is the acceleration of gravity, Hg, 9.80665iBeing the ith pneumatic layerThe potential height i is more than or equal to 1 and satisfies the following formula:
Figure BDA0003039728520000034
wherein Hg is0Is the potential height, R, of a pixeld287.05 is the dry to atmospheric ratio gas constant, PiIs the pressure of the ith pneumatic layer, P0Is Hg0Corresponding air pressure, TvThe atmospheric deficiency temperature satisfies the following formula:
Figure BDA0003039728520000035
wherein the content of the first and second substances,
Figure BDA0003039728520000036
the average humidity of each air pressure layer is taken as the average humidity,
Figure BDA0003039728520000037
the average temperature of each air pressure layer;
calculating corresponding influence parameter profile a according to the curvature radius of tangent points of the refractive index profile, the average altitude profile, the matched occultation event and the large ground level differencem：
am＝H+c+l
Wherein H is the average altitude, c is the tangent point curvature radius of each occultation event, and l is the ground level difference of each occultation event;
obtaining a forward bending angle profile alpha by adopting Abel integral forward calculationm；
Figure BDA0003039728520000038
Wherein, a0In order to cover the influence parameter at the cut point, ln (n) represents the natural logarithm of the refractive index n, and a represents the influence parameter;
obtaining an influencing parameter a from space-time data of occultation observationroInterpolation to the meterCalculated influence parameter profile amThe above.
As an improvement of the above method, the comparison statistical analysis is performed on the bending angle profile under exercise and the bending angle profile of the occultation observation data to obtain a bending angle relative deviation mean and a bending angle relative deviation standard deviation; the method specifically comprises the following steps:
the relative bend angle deviation Δ α is calculated from:
Figure BDA0003039728520000041
calculating the mean value of the relative deviation of the bending angle in the height range of 8-20km according to the formula
Figure BDA0003039728520000042
Comprises the following steps:
Figure BDA0003039728520000043
wherein u is the number of air pressure layers in the height range of 8-20km, i represents the ith air pressure layer in the height range, and Δ αiThe relative deviation of the bending angle of the ith air pressure layer;
the standard deviation sigma delta alpha of the relative bending angle in the height range of 8-20km is calculated by the following formula:
Figure BDA0003039728520000044
as an improvement of the above method, the absolute value Δ RT of the bright temperature difference value is:
ΔRT＝|RTro-RTm|
wherein, RTroFor positive performance of bright temperature, RTmThe light temperature was observed for a microwave radiometer.
As an improvement of the above method, the method detects whether two kinds of observation data meet the accuracy consistency standard based on the bending angle relative deviation mean value, the bending angle relative deviation standard deviation and the bright temperature difference value absolute value; judging coincidence, and selecting occultation observation data, microwave radiometer observation data matched with space and time and selecting the occultation observation data and the space and time data into a climate data set; the method specifically comprises the following steps:
based on mean value of relative deviation of bending angle
Figure BDA0003039728520000045
The standard deviation sigma delta alpha of the relative deviation of the bending angle and the absolute value delta RT of the bright temperature difference value judge whether the two kinds of observation data meet the accuracy consistency standard, if so, the two kinds of observation data are judged
Figure BDA0003039728520000046
And σ Δ α<2% and. DELTA.RT<And 1K, judging coincidence, and selecting occultation observation data, space-time matched microwave radiometer observation data and space-time data thereof into a climate data set.
As an improvement of the method, the microwave radiometer observation data is corrected by combining background atmospheric information and occultation observation data, and the occultation observation data, the corrected microwave radiometer observation data and the time-space data thereof are selected into a climate data set; the method specifically comprises the following steps:
reading the temperature profile, humidity profile and pressure profile of the background atmospheric pattern based on the world time and location longitude, latitude data of the matched occultation of the occultation event, and calculating the relative deviation mean value of the bending angle therefrom
Figure BDA0003039728520000051
And the bending angle relative deviation standard deviation sigma delta alpha;
if it is not
Figure BDA0003039728520000052
And σ Δ α<2%, respectively calculating correction factor profiles of observation parameters by using observation data and occultation observation data of a pixel point closest to the occultation event from observation pixels of the microwave radiometer conforming to the space-time matching standard, correcting the observation data of the microwave radiometer of each pixel point conforming to the occultation event space-time matching standard by using a correction factor, and selecting the occultation observation data and the corrected observation data of the microwave radiometer into a climate data set;
otherwise, judging the occultation event and the observation data of the matched microwave radiometer as bad data and deleting the data.
As an improvement of the method, the method generates a space-time continuous long-time-sequence climate data set fused with microwave radiometer and occultation data based on the climate data set; the method specifically comprises the following steps:
acquiring the bending angle of a occultation, brightness temperature data of a microwave radiometer and space-time data of the brightness temperature data as a primary fusion climate product from a climate data set;
acquiring the temperature, humidity, pressure and average altitude profiles of the occultation and microwave radiometers from a climate data set, and unifying all parameters into the same physical quantity and the same unit as a secondary fusion climate product; and further generating a space-time continuous long-time sequence climate data set fused by the microwave radiometer and the occultation data.
A occultation and microwave radiometer climate data cross-validation system, said system comprising: the system comprises a data acquisition module, a data preprocessing module, a data space-time matching module, a forward calculation module, a statistical comparison analysis module, a data quality consistency judgment module and a climate data fusion module; wherein the content of the first and second substances,
the data acquisition module is used for acquiring observation data of the microwave radiometer, occultation observation data and time-space data thereof; the observation data of the microwave radiometer comprise: bright temperature data, temperature profile, humidity profile and pressure profile; the occultation observation data includes: a curved angle profile, a temperature profile, a humidity profile, and a pressure profile;
the data preprocessing module is used for preprocessing the observation data of the microwave radiometer and the occultation observation data and rejecting abnormal observation data;
the data space-time matching module is used for carrying out data matching on the preprocessed observation data based on the space-time data to obtain observation data matched with the microwave radiometer and the occultation space-time;
the forward modeling calculation module is used for calculating the bending angle profile by adopting Abel integral forward modeling based on the temperature, humidity and pressure profiles of the microwave radiometer matched with space and time; the system is also used for calculating the brightness temperature by forward modeling through a radiation transmission model based on occultation temperature, humidity and pressure profiles matched in time and space;
the statistical comparison and analysis module is used for performing comparison statistical analysis on the bending angle profile in progress and the bending angle profile of the occultation observation data to obtain a bending angle relative deviation mean value and a bending angle relative deviation standard deviation; the microwave radiometer is also used for comparing and analyzing the actual bright temperature and the observed bright temperature of the microwave radiometer to obtain an absolute value of a bright temperature difference value;
the data quality consistency judging module is used for detecting whether the two kinds of observation data meet the precision consistency standard or not based on the bending angle relative deviation mean value, the bending angle relative deviation standard deviation and the bright temperature difference value absolute value; judging coincidence, and selecting occultation observation data, microwave radiometer observation data matched with space and time and selecting the occultation observation data and the space and time data into a climate data set; otherwise, correcting the observation data of the microwave radiometer by combining the background atmosphere information and the occultation observation data, and selecting the occultation observation data, the corrected observation data of the microwave radiometer and the time-space data of the observation data into a climate data set;
and the climate data fusion module is used for generating a time-space continuous long-time climate data set fused with the microwave radiometer and the occultation data based on the climate data set.
Compared with the prior art, the invention has the advantages that:
1. the method of the invention comprehensively uses occultation and microwave radiometer observation data to establish a climate data set;
2. the cross validation method of the invention uses the observation data of bending angle, brightness temperature and the like to evaluate the two climate data;
3. the cross validation method adopts occultation and microwave radiometer observation data to carry out cross validation, and mutually makes up the defects of time and space resolution and larger calibration error;
4. the method and the system are favorable for realizing the data fusion and the application of the occultation and microwave radiometer climate data.
Drawings
FIG. 1 is a flow chart of a method of cross-validation of occultation and microwave radiometer climate data of example 1 of the present invention;
fig. 2 is a schematic diagram of a cross-validation system for weather data of a masker and microwave radiometer according to example 2 of the present invention.
Detailed Description
The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and examples.
As shown in fig. 1, embodiment 1 of the present invention provides a method for cross-validating weather data of a occultation and microwave radiometer, including:
step S101) acquiring microwave radiometer, occultation observation data and time-space data thereof;
the observation data of the microwave radiometer comprise: bright temperature data, temperature profile, humidity profile and pressure profile; the occult observation data includes: a curved angle profile, a temperature profile, a humidity profile, and a pressure profile; the spatiotemporal data includes: the microwave radiometer observes the world time of data, the corresponding longitude, latitude and barometric pressure three-dimensional grid point data and the potential height of an observation pixel point; world time of occultation of the occultation event, longitude and latitude of occultation event position, curvature radius of tangent point, geodetic level gap, influence parameter, and average altitude profile thereof;
step S102) removing abnormal observation data through preprocessing according to the microwave radiometer and the occultation observation data;
step S103) matching the microwave radiometer and the occultation data according to the space-time data;
according to the time and position precision latitude of occulting event, the scanning time, longitude and latitude information of the microwave radiometer observation data pixel points, and according to the time difference delta t of occulting event and microwave radiometer observation pixel points, which is less than 90 minutes, and the distance difference delta s, which is less than 100km, the data matching is carried out, and the observation data matched with the occulting space and time of the microwave radiometer and the occulting is obtained;
Δt＝|tm-tro|
wherein, tmFor microwave radiometer data scanning time, troIs the occurence time of the occurence of the masquerading;
Figure BDA0003039728520000071
wherein the content of the first and second substances,
Figure BDA0003039728520000072
and λmFor the longitude and latitude of the microwave radiometric data pixel,
Figure BDA0003039728520000073
and λroThe longitude and latitude of the location where the occurance of the occult event is masked, and R is the average earth radius.
Step S104) calculating a bending angle profile through Abel integral forward modeling according to the matched temperature, humidity and pressure profiles of the microwave radiometer; the method specifically comprises the following steps:
step S104-1) calculating a refractive index profile according to the temperature, humidity and pressure profile data;
Figure BDA0003039728520000074
n＝1+N×10-6
wherein N is the refractive index, N is the refractive index, T is the temperature, PdAt atmospheric dry pressure, PwIs the water vapor pressure;
step S104-2) calculating a corresponding average altitude profile according to the temperature, humidity and pressure profile data; the present embodiment adopts the following formula to estimate the altitude H corresponding to each barometric legi：
Figure BDA0003039728520000075
Figure BDA0003039728520000076
Figure BDA0003039728520000077
Wherein, TvThe temperature of the air is the deficiency temperature of the air,
Figure BDA0003039728520000078
the average humidity of each layer is taken as the average humidity,
Figure BDA0003039728520000079
average temperature of each layer, Hg0Is the potential height of the pixel, HgiIs the potential height, R, of each air pressure layerd287.05 is the dry to atmospheric gas constant, g0The standard value for gravitational acceleration is the accurate measurement of the gravitational acceleration of the object at sea level at 45 ° latitude, P, 9.806650Is Hg0Corresponding air pressure, PiIs the data layer air pressure;
step S104-3) calculating corresponding influence parameter profile a according to the refractive index profile and the average altitude profile calculated in the steps S104-1) and S104-2), the curvature radius of the tangent point of the matched occultation event and the ground level gapm；
am＝H+c+l
Wherein H is the average altitude, c is the tangent point curvature radius of each occultation event, and l is the ground level difference of each occultation event;
step S104-4) obtaining a forward bending angle profile alpha by using Abel integral forward calculationm；
Figure BDA0003039728520000081
Wherein, a0To mask the influencing parameters at the tangent point.
Step S104-5) based on the influence parameter a of the occultation observationroAnd amWill observe the bending angle αroInterpolation to a on the calculated influence parameter profilem；
Step S105) comparing the forward bending angle profile with the occultation observation bending angle profile for statistical analysis; the method specifically comprises the following steps:
step S105-1) calculating a relative bending angle relative deviation profile delta alpha according to the bending angle profile obtained in the step S104);
Figure BDA0003039728520000082
step S105-2) calculating the relative deviation mean value of the bending angle within the height range of 8-20km
Figure BDA0003039728520000083
Figure BDA0003039728520000084
Wherein u is the number of data layers in the height range of 8-20km, namely the number of air pressure layers, and i is the index number of each layer;
step S105-2) calculating the relative deviation standard deviation sigma delta alpha of the bending angle within the height range of 8-20 km;
Figure BDA0003039728520000085
step S106) calculating the brightness temperature RT of the observation channel in the 8-20km height range through forward modeling of a radiation transmission model according to the matched occultation temperature, humidity and pressure profilesro(ii) a As an example, the radiation transmission model can be selected from an atmospheric radiation transmission model (CRTM) or an atmospheric rapid radiation transmission model (RTTOV).
Step S107) forward bright temperature RTroObserving the bright temperature RT with a microwave radiometermCarrying out comparative analysis; obtaining the absolute value delta RT of the bright temperature difference value:
ΔRT＝|RTro-RTm|
step S108) detecting whether the two kinds of observed data accord with the accuracy consistency standard according to the error parameters calculated in the steps S105) and S107);
if it is not
Figure BDA0003039728520000095
And σ Δ α<2% and. DELTA.RT<1K, judging that the microwave radiometer and the occultation observation data meet the consistency of data quality; and if any error does not meet the corresponding index, judging that the two kinds of observation data do not meet the requirement of data quality consistency.
Step S109) if the detection result of the step S108) is 'yes', the occultation observation data, the microwave radiometer observation data within the space-time matching standard range and the space-time data thereof are selected into a climate data set;
step S110) if the detection result of the step S108) is 'No', correcting the observation data of the microwave radiometer by combining the background atmospheric information and the occultation data so as to obtain corrected observation data and space-time data; the method specifically comprises the following steps:
step S110-1) reading the temperature, humidity and pressure profiles of a background atmosphere mode (such as an ECWMF reanalysis mode) by using the occurrence time and the position longitude and latitude data of the matched occultation event;
step S110-2) using the temperature, humidity and pressure profiles of the background atmosphere read as above as input parameters, and calculating the bending angle error parameter by the method of steps S104) and S105)
Figure BDA0003039728520000091
And σ Δ α;
step S110-3) if the above calculation is made
Figure BDA0003039728520000092
And σ Δ α<2 percent, showing that the occultation data meets the precision requirement of climate monitoring, and then using the temperature, humidity and pressure profile of the occultation and the positive calculated bright temperature RTroAs reference data, the corresponding observation data of the microwave radiometer are corrected. The specific method comprises the following steps:
and respectively calculating the correction factor profiles of the observation parameters by using the observation data and the occultation reference data of the pixel point closest to the occultation event in the observation pixels of the microwave radiometer conforming to the space-time matching standard:
ΔT＝Tm-Tro，Δq＝qm-qro，ΔP＝Pm-Pro，ΔRT＝RTm-RTro；
and then correcting the observation data of each pixel point meeting the occultation event space-time matching standard by using a correction factor:
Figure BDA0003039728520000093
then, selecting occultation observation data and corrected observation data of the microwave radiometer into a climate data set;
step S110-4) if the above calculation is made
Figure BDA0003039728520000094
Or the sigma delta alpha is more than or equal to 2 percent, which indicates that the occultation data does not meet the precision requirement of climate monitoring, and the occultation event and the observation data of the matched microwave radiometer are judged to be bad data and abandoned.
Step S111) generating a space-time continuous long-time sequence climate data set fused by the microwave radiometer and the occultation data.
S111-1) selecting a occultation bending angle and a microwave radiometer brightness temperature selected into a climate data set and relevant space-time data of the occultation bending angle and the microwave radiometer brightness temperature as a primary fusion climate product;
and S111-2) selecting the occultation of the selected climate data set and the temperature, humidity, pressure and average altitude profile of the microwave radiometer, and unifying all parameters into the same physical quantity and the same unit to be used as a secondary fusion climate product.
The observation data of the occultation and microwave radiometer can be cross-verified, and the defects of insufficient time and space resolution and large calibration error are mutually compensated. Namely, the observation data of the microwave radiometer can make up the defects of low global coverage density and no space-time continuity of occultation observation data; the occultation can correct the data 'drift' problem caused by the calibration error of different microwave radiometers of different satellites. Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.
Example 2
As shown in fig. 2, embodiment 2 of the present invention proposes a cross-validation system for weather data of a masker and microwave radiometer, which comprises in a system 200: the system comprises a data acquisition module 201, a data preprocessing module 202, a data space-time matching module 203, a forward calculation module 204, a statistic comparison analysis module 205, a data quality consistency judgment module 206 and a climate data fusion module 207; wherein the content of the first and second substances,
the data acquisition module 201 is configured to acquire observation data of the microwave radiometer, occultation observation data, and time-space data thereof; the observation data of the microwave radiometer comprise: bright temperature data, temperature profile, humidity profile and pressure profile; the occultation observation data includes: a curved angle profile, a temperature profile, a humidity profile, and a pressure profile;
the data preprocessing module 202 is configured to preprocess the observation data of the microwave radiometer and the occultation observation data, and reject abnormal observation data;
the data space-time matching module 203 is used for performing data matching on the preprocessed observation data based on the space-time data to obtain observation data matched with the microwave radiometer and the occultation space-time;
the forward calculation module 204 is configured to calculate a bending angle profile by Abel integral forward calculation based on the temperature, humidity, and pressure profiles of the microwave radiometer matched in time and space; the system is also used for calculating the brightness temperature by forward modeling through a radiation transmission model based on occultation temperature, humidity and pressure profiles matched in time and space;
the statistical comparison and analysis module 205 is configured to perform comparison and statistical analysis on the bending angle profile being performed and the bending angle profile of the occultation observation data to obtain a bending angle relative deviation mean and a bending angle relative deviation standard deviation; the microwave radiometer is also used for comparing and analyzing the actual bright temperature and the observed bright temperature of the microwave radiometer to obtain an absolute value of a bright temperature difference value;
the data quality consistency judging module 206 is configured to detect whether two types of observation data meet a precision consistency standard based on a bending angle relative deviation mean value, a bending angle relative deviation standard deviation and a bright temperature difference value absolute value; judging coincidence, and selecting occultation observation data, microwave radiometer observation data matched with space and time and selecting the occultation observation data and the space and time data into a climate data set; otherwise, correcting the observation data of the microwave radiometer by combining the background atmosphere information and the occultation observation data, and selecting the occultation observation data, the corrected observation data of the microwave radiometer and the time-space data of the observation data into a climate data set;
the climate data fusion module 207 is configured to generate a time-space continuous long-time climate data set fused with the microwave radiometer and the occultation data based on the climate data set.
The specific implementation process of each module is the same as that of the embodiment 1.
Embodiment 3 of the present invention proposes a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor implements the method of embodiment 1 described above when executing the computer program.
Embodiment 4 of the present invention proposes a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to execute the method of embodiment 1 described above.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (10)

1. A method of cross-validation of occultation and microwave radiometer climate data, the method comprising:
acquiring observation data of a microwave radiometer, occultation observation data and time-space data thereof; the observation data of the microwave radiometer comprise: bright temperature data, temperature profile, humidity profile and pressure profile; the occultation observation data includes: a curved angle profile, a temperature profile, a humidity profile, and a pressure profile;
preprocessing the observation data of the microwave radiometer and the occultation observation data, and rejecting abnormal observation data;
carrying out data matching on the preprocessed observation data based on the space-time data to obtain observation data matched with the microwave radiometer and the occultation space-time;
calculating a bending angle profile by adopting Abel integral forward modeling based on temperature, humidity and pressure profiles of the microwave radiometer matched with time and space;
comparing the calculated bending angle profile with the bending angle profile of the occultation observation data, and performing statistical analysis to obtain a bending angle relative deviation mean value and a bending angle relative deviation standard deviation;
based on the occultation temperature, humidity and pressure profiles of space-time matching, forward modeling is adopted to calculate the brightness temperature by adopting a radiation transmission model;
comparing and analyzing the actual bright temperature with the bright temperature observed by the microwave radiometer to obtain an absolute value of a bright temperature difference value;
detecting whether the two kinds of observation data meet the precision consistency standard or not based on the bending angle relative deviation mean value, the bending angle relative deviation standard deviation and the bright temperature difference value absolute value; judging coincidence, and selecting occultation observation data, microwave radiometer observation data matched with space and time and selecting the occultation observation data and the space and time data into a climate data set; otherwise, correcting the observation data of the microwave radiometer by combining the background atmosphere information and the occultation observation data, and selecting the occultation observation data, the corrected observation data of the microwave radiometer and the time-space data of the observation data into a climate data set;
and generating a space-time continuous long-time sequence climate data set fused with the microwave radiometer and the occultation data based on the climate data set.
2. The method of cross-validation of occultation and microwave radiometer climate data according to claim 1, wherein the spatiotemporal data comprises: the microwave radiometer observes the world time of data, the corresponding longitude, latitude and barometric pressure three-dimensional grid point data and the potential height of an observation pixel point; the world time of the occultation event, the longitude and latitude of the occultation event location, the radius of curvature of the tangent point, the geodesic gap, the influencing parameters and their average altitude profile.
3. The occultation and microwave radiometer climate data cross-validation method according to claim 2, wherein the pre-processed observation data is subjected to data matching based on the spatiotemporal data to obtain observation data matched with the occultation and spatiotemporal; the method specifically comprises the following steps:
world time t based on occultation of occultation eventroAnd the universal time t of observation data of the microwave radiometermThe time difference Δ t is calculated as:
Δt＝|tm-tro|；
occultation event location longitude based
Figure FDA0003039728510000021
And latitude λroLongitude of observation data pixel of microwave radiometer
Figure FDA0003039728510000022
And latitude λmThe calculated distance difference Δ s is:
Figure FDA0003039728510000023
wherein R is the average earth radius;
and carrying out data matching on the preprocessed data according to a space-time matching standard that the time difference delta t is less than 90 minutes and the distance difference delta s is less than 100km to obtain observation data matched with the microwave radiometer and the occultation space-time.
4. The occultation and microwave radiometer climate data cross-validation method according to claim 3, wherein the space-time matching based microwave radiometer temperature, humidity and pressure profiles are calculated by Abel integral forward modeling; the method specifically comprises the following steps:
calculating a refractive index profile from the temperature, humidity and pressure profile data;
n＝1+N×10-6
wherein N is a refractive index, N is a refractive index, and N satisfies the following formula:
Figure FDA0003039728510000024
wherein T is temperature, PdAt atmospheric dry pressure, PwIs the water vapor pressure;
calculating the altitude H corresponding to the ith air pressure layer according to the following formulaiAnd further obtaining an average altitude profile:
Figure FDA0003039728510000025
wherein, the standard value g of the gravity acceleration0G is the acceleration of gravity, Hg, 9.80665iThe potential height of the ith air pressure layer is represented by i which is more than or equal to 1 and satisfies the following formula:
Figure FDA0003039728510000026
wherein Hg is0Is the potential height, R, of a pixeld287.05 is the dry to atmospheric ratio gas constant, PiIs the pressure of the ith pneumatic layer, P0Is Hg0Corresponding air pressure, TvThe atmospheric deficiency temperature satisfies the following formula:
Figure FDA0003039728510000027
wherein the content of the first and second substances,
Figure FDA0003039728510000028
the average humidity of each air pressure layer is taken as the average humidity,
Figure FDA0003039728510000029
the average temperature of each air pressure layer;
calculating corresponding influence parameter profile a according to the curvature radius of tangent points of the refractive index profile, the average altitude profile, the matched occultation event and the large ground level differencem：
am＝H+c+l
Wherein H is the average altitude, c is the tangent point curvature radius of each occultation event, and l is the ground level difference of each occultation event;
obtaining a forward bending angle profile alpha by adopting Abel integral forward calculationm；
Figure FDA0003039728510000031
Wherein, a0In order to cover the influence parameter at the cut point, ln (n) represents the natural logarithm of the refractive index n, and a represents the influence parameter;
obtaining an influencing parameter a from space-time data of occultation observationroInterpolation to the calculated influencing parameter profile amThe above.
5. The occultation and microwave radiometer climate data cross-validation method according to claim 4, wherein the comparison statistical analysis is performed on the bending angle profile being worked on and the bending angle profile of the occultation observation data to obtain a bending angle relative deviation mean and a bending angle relative deviation standard deviation; the method specifically comprises the following steps:
the relative bend angle deviation Δ α is calculated from:
Figure FDA0003039728510000032
calculating the mean value of the relative deviation of the bending angle in the height range of 8-20km according to the formula
Figure FDA0003039728510000033
Comprises the following steps:
Figure FDA0003039728510000034
wherein u is the number of air pressure layers in the height range of 8-20km, i represents the ith air pressure layer in the height range, and Δ αiThe relative deviation of the bending angle of the ith air pressure layer;
the standard deviation sigma delta alpha of the relative bending angle in the height range of 8-20km is calculated by the following formula:
Figure FDA0003039728510000035
6. the method of cross-validation of occultation and microwave radiometer climate data according to claim 5, wherein the absolute value of the bright temperature difference Δ RT is:
ΔRT＝|RTro-RTm|
wherein, RTroFor positive performance of bright temperature, RTmThe light temperature was observed for a microwave radiometer.
7. The occultation and microwave radiometer climate data cross-validation method according to claim 6, wherein the method comprises detecting whether two kinds of observation data meet the accuracy consistency standard based on the bending angle relative deviation mean value, the bending angle relative deviation standard deviation and the bright temperature difference value absolute value; judging coincidence, and selecting occultation observation data, microwave radiometer observation data matched with space and time and selecting the occultation observation data and the space and time data into a climate data set; the method specifically comprises the following steps:
based on mean value of relative deviation of bending angle
Figure FDA0003039728510000036
The standard deviation sigma delta alpha of the relative deviation of the bending angle and the absolute value delta RT of the bright temperature difference value judge whether the two kinds of observation data meet the accuracy consistency standard, if so, the two kinds of observation data are judged
Figure FDA0003039728510000037
And the sigma delta alpha is less than 2 percent, the delta RT is less than 1K, the judgment is in accordance, and the occultation observation data, the microwave radiometer observation data matched with the space and the space time data thereof are selected into a climate data set.
8. The occultation and microwave radiometer climate data cross-validation method according to claim 7, wherein the microwave radiometer observation data is modified in combination with the background atmospheric information and the occultation observation data, the modified microwave radiometer observation data and the time-space data thereof are selected into a climate data set; the method specifically comprises the following steps:
reading the temperature profile, humidity profile and pressure profile of the background atmospheric pattern based on the world time and location longitude, latitude data of the matched occultation of the occultation event, and calculating the relative deviation mean value of the bending angle therefrom
Figure FDA0003039728510000041
And the bending angle relative deviation standard deviation sigma delta alpha;
if it is not
Figure FDA0003039728510000042
And sigma delta alpha is less than 2%, respectively calculating correction factor profiles of all observation parameters by using observation data and occultation observation data of a pixel point closest to the occultation event from the observation pixels of the microwave radiometer conforming to the space-time matching standard, correcting the observation data of the microwave radiometer of each pixel point conforming to the space-time matching standard of the occultation event by using a correction factor, and selecting the occultation observation data and the corrected observation data of the microwave radiometer into a climate data set;
otherwise, judging the occultation event and the observation data of the matched microwave radiometer as bad data and deleting the data.
9. The occultation and microwave radiometer climate data cross-validation method according to claim 8, wherein the generating a time-space continuous long time sequence climate data set fused by microwave radiometer and occultation data based on the climate data set; the method specifically comprises the following steps:
acquiring the bending angle of a occultation, brightness temperature data of a microwave radiometer and space-time data of the brightness temperature data as a primary fusion climate product from a climate data set;
acquiring the temperature, humidity, pressure and average altitude profiles of the occultation and microwave radiometers from a climate data set, and unifying all parameters into the same physical quantity and the same unit as a secondary fusion climate product; and further generating a space-time continuous long-time sequence climate data set fused by the microwave radiometer and the occultation data.
10. A occultation and microwave radiometer climate data cross-validation system, said system comprising: the system comprises a data acquisition module, a data preprocessing module, a data space-time matching module, a forward calculation module, a statistical comparison analysis module, a data quality consistency judgment module and a climate data fusion module; wherein the content of the first and second substances,
the data acquisition module is used for acquiring observation data of the microwave radiometer, occultation observation data and time-space data thereof; the observation data of the microwave radiometer comprise: bright temperature data, temperature profile, humidity profile and pressure profile; the occultation observation data includes: a curved angle profile, a temperature profile, a humidity profile, and a pressure profile;
the data preprocessing module is used for preprocessing the observation data of the microwave radiometer and the occultation observation data and rejecting abnormal observation data;
the data space-time matching module is used for carrying out data matching on the preprocessed observation data based on the space-time data to obtain observation data matched with the microwave radiometer and the occultation space-time;
the forward modeling calculation module is used for calculating the bending angle profile by adopting Abel integral forward modeling based on the temperature, humidity and pressure profiles of the microwave radiometer matched with space and time; the system is also used for calculating the brightness temperature by forward modeling through a radiation transmission model based on occultation temperature, humidity and pressure profiles matched in time and space;
the statistical comparison and analysis module is used for performing comparison statistical analysis on the bending angle profile in progress and the bending angle profile of the occultation observation data to obtain a bending angle relative deviation mean value and a bending angle relative deviation standard deviation; the microwave radiometer is also used for comparing and analyzing the actual bright temperature and the observed bright temperature of the microwave radiometer to obtain an absolute value of a bright temperature difference value;
the data quality consistency judging module is used for detecting whether the two kinds of observation data meet the precision consistency standard or not based on the bending angle relative deviation mean value, the bending angle relative deviation standard deviation and the bright temperature difference value absolute value; judging coincidence, and selecting occultation observation data, microwave radiometer observation data matched with space and time and selecting the occultation observation data and the space and time data into a climate data set; otherwise, correcting the observation data of the microwave radiometer by combining the background atmosphere information and the occultation observation data, and selecting the occultation observation data, the corrected observation data of the microwave radiometer and the time-space data of the observation data into a climate data set;
and the climate data fusion module is used for generating a time-space continuous long-time climate data set fused with the microwave radiometer and the occultation data based on the climate data set.
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